Rates of transformation to AML/MDS in MPN patients by age and time since diagnosis: a nationwide register-based matched cohort study

Supplementary material

1 Research objective

We aimed to model transformation rates simultaneously over attained age or time since diagnosis for MPN patients overall, and by subtypes. Further subanalysis was carried out specific to cytoreductive treatments. Additional summary was also provided for genetic information.

2 Settings

Study design: cohort study

Data sources:

• the National Cancer Register (for MPN, other hematological malignancies)
• the National Inpatient Register (hospital admissions), the National Outpatient Register (specialist visits) (for MPN and AML/MDS diagnoses)
• the National Causes of Deaths Register (for AML/MDS diagnoses and other causes of deaths)
• the National Prescribed Drugs Register (for cytoreductive drugs)
• the Total Population Register (for demographic data)
• the MPN Quality Register (for genetic data)

Study period: three study periods are covered in this study:

• for describing transformation rates overall and by subtypes, the diagnosis period is 2001 - 2021
• for describing transformation rates by exposure to cytoreductive drugs, the diagnosis period is 2006 - 2021
• for summarising patient numbers by somatic mutations JAK2, CALR, MPL, the diagnosis period is 2008 - 2021

Index date: at 3 months post MPN date date. Individuals were excluded if prior to the index date, they transformed to AML/MDS, developed other hematological malignancy, or they emigrated, or they died.

Event of interest: three types of events were analysed separately: AML/MDS, AML, MDS. For the event AML, patients were not censored if they were diagnosed with MDS prior to AML, whereas for the MDS, patients were censored if they were diagnosed with AML prior to MDS.

End of follow-up: individuals were followed until the outcome of interest or censoring due to above, or due to emigration, due to death from other causes, or due to the end of follow-up (December 31, 2022); whichever occurred first.

3 Main model

Fitted the following flexible parametric survival model on the log-hazard scale with two time-scales:

\[ \begin{align} \log h & = s(t_1; \gamma_1) + s(t_2; \gamma_2) \end{align} \] where \(t_1\) is time since the index date and \(t_2\) is attained age. Functions \(s\) represent restricted cubic splines with \(\gamma\) as corresponding parameters. Optimal number of knots for the spline functions were chosen based on AIC and BIC of the models.

Stata code for the model:

stmt mpn, ///
         time1(df(3) logtoff) ///
         time2(df(3) logtoff start(start_age))

Click here for stata code for predicting thrombosis rates

/* predict hazard rates for each time-point of time1, time2 and age0 */
local n=1
local datalist ""
forvalues a0= 30 30.25 : 90 {
    qui clear
    qui set obs 401 
    qui gen age_start =`a0'             // a0: age at index
    qui range time1 0 20 401            // t1: time on study
    qui gen time2 = time1 + age_start   // t2: attained age
    qui gen _d = .
    qui gen _t = .

    /* predict hazard rates */
    qui predict h, h time1var(time1) time2var(time2) per(1000) ci
     
  qui tempfile temppred`n'
  qui save `temppred`n''
  local datalist `datalist' `temppred`n''
  local n=`n'+1
 }

qui clear 
qui set obs 0 
qui append using `datalist' 
qui order age_start time2
    
keep time1 time2 age_start h*

4 Results

Cohort characteristics

Table 4.1: Characteristics of Swedish patients diagnosed during 2001-2021 with myeloproliferative neoplasms. MPN=myeloproliferative neoplasm, PV=polycythemia vera, ET=essential thrombocythemia, PMF=primary myelofibrosis, MPN-U=myeloproliferative neoplasm unclassifiable.

	PV (N=7156)	ET (N=6810)	PMF (N=1080)	MPN-U (N=2784)	Total (N=17830)
Sex
Female	3178 (44.4%)	4200 (61.7%)	452 (41.9%)	1487 (53.4%)	9317 (52.3%)
Male	3978 (55.6%)	2610 (38.3%)	628 (58.1%)	1297 (46.6%)	8513 (47.7%)
Age at diagnosis
Median (Q1, Q3)	70.9 (60.8, 78.2)	68.2 (55.5, 77.3)	71.6 (62.7, 78.7)	71.7 (60.8, 79.3)	70.1 (59.0, 78.0)
18-49	684 (9.6%)	1192 (17.5%)	96 (8.9%)	317 (11.4%)	2289 (12.8%)
50-59	1007 (14.1%)	1011 (14.8%)	114 (10.6%)	348 (12.5%)	2480 (13.9%)
60-69	1718 (24.0%)	1504 (22.1%)	280 (25.9%)	596 (21.4%)	4098 (23.0%)
70-79	2327 (32.5%)	1884 (27.7%)	370 (34.3%)	885 (31.8%)	5466 (30.7%)
80-90	1420 (19.8%)	1219 (17.9%)	220 (20.4%)	638 (22.9%)	3497 (19.6%)
Calendar period of diagnosis
2001-2010	3171 (44.3%)	2635 (38.7%)	325 (30.1%)	1675 (60.2%)	7806 (43.8%)
2011-2021	3985 (55.7%)	4175 (61.3%)	755 (69.9%)	1109 (39.8%)	10024 (56.2%)
Event of interest
AML/MDS	291 (4.1%)	315 (4.6%)	207 (19.2%)	407 (14.6%)	1220 (6.8%)
AML	190 (2.7%)	191 (2.8%)	135 (12.5%)	183 (6.6%)	699 (3.9%)
MDS	115 (1.6%)	166 (2.4%)	83 (7.7%)	254 (9.1%)	618 (3.5%)

Transformation rates

All MPNs

AML/MDS

Figure 4.1: Rates of transformation to AML/MDS per 1000 person-years in Swedish MPN patients. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date with different ages at index date. Panel (C): rates over attained age for different times since index date.

AML

Figure 4.2: Rates of transformation to AML per 1000 person-years in Swedish MPN patients. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date for different ages at index date. Panel (C): rates over attained age for different times since index date.

MDS

Figure 4.3: Rates of transformation to MDS per 1000 person-years in Swedish MPN patients. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date for different ages at index date. Panel (C): rates over attained age for different times since index date.

PV

AML/MDS

Figure 4.4: Rates of transformation to AML/MDS per 1000 person-years in patients with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

AML

Figure 4.5: Rates of transformation to AML per 1000 person-years in patients with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

MDS

Figure 4.6: Rates of transformation to MDS per 1000 person-years in patients with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

ET

AML/MDS

Figure 4.7: Rates of transformation to AML/MDS per 1000 person-years in patients with essential thrombocythemia (ET). Panel (A): rates for patients along time since index date with different ages at index date. Panel (B): rates over attained age for ET patients with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

AML

Figure 4.8: Rates of transformation to AML per 1000 person-years in patients with essential thrombocythemia (ET). Panel (A): rates over attained age for ET patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

MDS

Figure 4.9: Rates of transformation to MDS per 1000 person-years in patients with essential thrombocythemia (ET). Panel (A): rates over attained age for ET patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

PMF

AML/MDS

Figure 4.10: Rates of transformation to AML/MDS per 1000 person-years in patients with primary myelofibrosis (PMF). Panel (A): rates over attained age for PMF patients with different ages at index date.Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

AML

Figure 4.11: Rates of transformation to AML per 1000 person-years in patients with primary myelofibrosis (PMF). Panel (C): rates over attained age for PMF patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

MDS

Figure 4.12: Rates of transformation to MDS per 1000 person-years in patients with primary myelofibrosis (PMF). Panel (A): rates over attained age for PMF patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

MPN-U

AML/MDS

Figure 4.13: Rates of transformation to AML/MDS per 1000 person-years in patients with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

AML

Figure 4.14: Rates of transformation to AML per 1000 person-years in patients with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

MDS

Figure 4.15: Rates of transformation to MDS per 1000 person-years in patients with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

Data

Below are few selected rows from the dataset containing estimated thrombosis rates and hazard ratios for all MPNs and subtypes for any thrombosis, arterial thrombosis and venous thrombosis. If you wish to see full data (size ~200 Mb), the following download link will provide the excel file: https://github.com/nurbatyr/Suppl-material-thrombosis-rates-in-MPNs-over-2ts/releases/download/thromb-rates-main/011_021_estimated_thrombosis_rates.xlsx

Transformation rates by sex

All MPNs

AML/MDS

Figure 4.16: Rates of transformation to AML/MDS per 1000 person-years in Swedish MPN patients by sex. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date with different ages at index date. Panel (C): rates over attained age for different times since index date.

AML

Figure 4.17: Rates of transformation to AML per 1000 person-years in Swedish MPN patients by sex. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date for different ages at index date. Panel (C): rates over attained age for different times since index date.

MDS

Figure 4.18: Rates of transformation to MDS per 1000 person-years in Swedish MPN patients by sex. Panel (A): rates over attained age for different ages at index date. Panel (B): rates along time since index date for different ages at index date. Panel (C): rates over attained age for different times since index date.

PV

AML/MDS

Figure 4.19: Rates of transformation to AML/MDS per 1000 person-years in males and females with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

AML

Figure 4.20: Rates of transformation to AML per 1000 person-years in males and females with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

MDS

Figure 4.21: Rates of transformation to MDS per 1000 person-years in males and females with polycythemia vera (PV). Panel (A): rates over attained age for PV patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PV patients with different times since index date.

ET

AML/MDS

Figure 4.22: Rates of transformation to AML/MDS per 1000 person-years in males and females with essential thrombocythemia (ET). Panel (A): rates for patients along time since index date with different ages at index date. Panel (B): rates over attained age for ET patients with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

AML

Figure 4.23: Rates of transformation to AML per 1000 person-years in males and females with essential thrombocythemia (ET). Panel (A): rates over attained age for ET patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

MDS

Figure 4.24: Rates of transformation to MDS per 1000 person-years in males and females with essential thrombocythemia (ET). Panel (A): rates over attained age for ET patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for ET patients with different times since index date.

PMF

AML/MDS

Figure 4.25: Rates of transformation to AML/MDS per 1000 person-years in males and females with primary myelofibrosis (PMF). Panel (A): rates over attained age for PMF patients with different ages at index date.Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

AML

Figure 4.26: Rates of transformation to AML per 1000 person-years in males and females with primary myelofibrosis (PMF). Panel (C): rates over attained age for PMF patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

MDS

Figure 4.27: Rates of transformation to MDS per 1000 person-years in males and females with primary myelofibrosis (PMF). Panel (A): rates over attained age for PMF patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for PMF patients with different times since index date.

MPN-U

AML/MDS

Figure 4.28: Rates of transformation to AML/MDS per 1000 person-years in males and females with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

AML

Figure 4.29: Rates of transformation to AML per 1000 person-years in males and females with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

MDS

Figure 4.30: Rates of transformation to MDS per 1000 person-years in males and females with MPN-unclassifiable (MPN-U). Panel (A): rates over attained age for MPN-U patients with different ages at index date. Panel (B): rates for patients along time since index date with different ages at index date. Panel (C): rates over attained age for MPN-U patients with different times since index date.

Data

Below are few selected rows from the dataset containing estimated thrombosis rates and hazard ratios for all MPNs and subtypes for any thrombosis, arterial thrombosis and venous thrombosis. If you wish to see full data (size ~200 Mb), the following download link will provide the excel file: https://github.com/nurbatyr/Suppl-material-thrombosis-rates-in-MPNs-over-2ts/releases/download/thromb-rates-main/041_051_estimated_thrombosis_rates.xlsx

5 Transformation rates by treatments in MPNs

We investigated further the patterns of transformation rates over two time-scales in MPN patients with cytoreductive treatments.

The cytoreductive treatment constituted any of the following drugs that were collected after the MPN date and before the end of follow-up: Interferon (ATC: L03AB11, L03AB10), Hydroxyurea (ATC: L01XX05), Jakavi (ATC: L01EJ01), Anagrelide (ATC: L01XX35), Busulfan (ATC: L01AB01).

Since the Prescribed Drugs Register was established in July 2005, we looked at MPN patients diagnosed during 2006-2021. A time-varying treatment variable was created based on the following criteria:

• “0” = No cytoreductive treatment,
• “1” = 2 collections of Interferon,
• “2” = 2 collections of Hydroxyurea,
• “3” = 2 collections of each Interferon and Hydroxyurea,
• “4” = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan

Patients can go from treatment state 0 to 1, from 0 to 2, from 1 to 3, from 2 to 3, and reach state 4 from any state. Note: starting treatment state can be any of the above. For the analysis, only treatment states that were at index date and beyond were included.

Model

Fitted the following model:

\[ \begin{align} \log h & = s(t_1; \gamma_1) + s(t_2; \gamma_2) + \beta_{trt1} \cdot I_{trt1} + \beta_{trt2} \cdot I_{trt2} + \beta_{trt3} \cdot I_{trt3} + \beta_{trt4} \cdot I_{trt4} + \\ & + s(t_1; \gamma_3) \cdot (I_{trt1} + I_{trt2} + I_{trt3} + I_{trt4})) \end{align} \] where \(t_1\) is time since index date, \(t_2\) is attained age, \(I_{trt}\) is a time-varying indicator variable for the corresponding treatment state.

Stata code for the model:

stmt trt1 trt2 trt3 trt4, ///
    time1(df(3) logtoff tvc(trt1 trt2 trt3 trt4) dftvc(trt1:1 trt2:1 trt3:1 trt4:1)) ///
    time2(df(3) logtoff start(start_age))

Results

Table 5.1: MPN-patients with diagnosis during 2006-2021 at different treatment states after index date (3 months post MPN-diagnosis) during the follow-up where the event of interest is AML/MDS, AML and MDS, respectively. Treatment state is a time-varying covariate, so patients can go from 0 to 1, from 0 to 2, from 1 to 3, from 2 to 3, and reach state 4 from any state, where ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan. Note: starting treatment state can be any of the above.

Treatment state	Person-years	Number of events	N	Event
0 = No cytoreductive treatment	35,361	282	11,245	AML/MDS
1 = 2 collections of Interferon	3,477	12	768
2 = 2 collections of Hydroxyurea	38,325	399	7,677
3 = 2 collections of each Interferon and Hydroxyurea	2,015	16	462
4 = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan	5,277	129	1,342
0 = No cytoreductive treatment	35,781	103	11,245	AML
1 = 2 collections of Interferon	3,498	4	769
2 = 2 collections of Hydroxyurea	38,693	248	7,709
3 = 2 collections of each Interferon and Hydroxyurea	2,023	12	464
4 = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan	5,399	90	1,367
0 = No cytoreductive treatment	35,361	196	11,245	MDS
1 = 2 collections of Interferon	3,477	9	768
2 = 2 collections of Hydroxyurea	38,325	185	7,677
3 = 2 collections of each Interferon and Hydroxyurea	2,015	7	462
4 = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan	5,277	47	1,342
Total number of patients in the cohort N=13986.

AML/MDS

By attained age

Figure 5.1: Rates of transformation to AML/MDS per 1000 person-years by attained age for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By time since index date

Figure 5.2: Rates of transformation to AML/MDS per 1000 person-years by time since index date for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By attained age for times since index date

Figure 5.3: Rates of transformation to AML/MDS per 1000 person-years by attained age for different times since index date for MPN patients at treatments states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

AML

By attained age

Figure 5.4: Rates of transformation to AML per 1000 person-years by attained age for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By time since index date

Figure 5.5: Rates of transformation to AML per 1000 person-years by time since index date for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By attained age for times since index date

Figure 5.6: Rates of transformation to AML per 1000 person-years by attained age for different times since index date for MPN patients at treatments states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

MDS

By attained age

Figure 5.7: Rates of transformation to MDS per 1000 person-years by attained age for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By time since index date

Figure 5.8: Rates of transformation to MDS per 1000 person-years by time since index date for MPN patients at treatment states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

By attained age for times since index date

Figure 5.9: Rates of transformation to MDS per 1000 person-years by attained age for different times since index date for MPN patients at treatments states: ‘0’ = No cytoreductive treatment, ‘1’ = 2 collections of Interferon, ‘2’ = 2 collections of Hydroxyurea, ‘3’ = 2 collections of each Interferon and Hydroxyurea, ‘4’ = 2 collections of Jakavi or Anagrelide, or 1 collection of Busulfan.

Data

Below are few selected rows from the dataset containing estimated thrombosis rates for all MPNs with exposure to anticoagulant treatment and for any thrombosis as event of interest. If you wish to see full data (size ~15 Mb), the following download link will provide the excel file: https://github.com/nurbatyr/Suppl-material-thrombosis-rates-in-MPNs-over-2ts/releases/download/thromb-rates-by-anticoag-trt/031_estimated_thrombosis_rates_by_cyt_anticoag.xlsx

Note: trt0 = ‘No aspirin, no anticoagulants’, trt1 = ‘Aspirin/Clopidogrel’, trt2 = ‘Strong anticoagulants’.

6 Somatic mutations

Information on gene mutations was obtained from the Swedish MPN Quality Register, which was established in 2008. Due to sparsity and potential unreliability of data, it was not possible to fit any models. Here we provide only summary statistics for JAK2, CALR and MPL mutations, and overall.

Table 6.1: Characteristics of patients with myeloproliferative neoplasms by somatic mutation status (cohort 2008-2021) with event of interest as AML/MDS. MPN=myeloproliferative neoplasm, PV=polycythemia vera, ET=essential thrombocythemia, PMF=primary myelofibrosis, MPN-U=myeloproliferative neoplasm unclassifiable.

	JAK2			CALR		MPL		JAK2, CALR, MPL
	Pos (N=4892)	Neg (N=871)	Missing (N=877)	Pos (N=370)	Neg/Missing (N=6270)	Pos (N=107)	Neg/Missing (N=6533)	Triple positive (N=7)	Overall (N=6640)
Sex
Female	2635 (53.9%)	450 (51.7%)	444 (50.6%)	174 (47.0%)	3355 (53.5%)	65 (60.7%)	3464 (53.0%)	4 (57.1%)	3529 (53.1%)
Male	2257 (46.1%)	421 (48.3%)	433 (49.4%)	196 (53.0%)	2915 (46.5%)	42 (39.3%)	3069 (47.0%)	3 (42.9%)	3111 (46.9%)
Age at diagnosis
Median (Q1, Q3)	70.2 (60.4, 77.1)	68.6 (56.0, 76.3)	69.7 (58.1, 78.4)	66.3 (54.5, 75.7)	70.1 (59.8, 77.3)	70.1 (56.4, 76.2)	69.9 (59.5, 77.2)	66.4 (58.6, 70.4)	69.9 (59.5, 77.2)
18-49	560 (11.4%)	146 (16.8%)	138 (15.7%)	65 (17.6%)	779 (12.4%)	12 (11.2%)	832 (12.7%)	0 (0.0%)	844 (12.7%)
50-59	636 (13.0%)	132 (15.2%)	115 (13.1%)	70 (18.9%)	813 (13.0%)	18 (16.8%)	865 (13.2%)	2 (28.6%)	883 (13.3%)
60-69	1214 (24.8%)	193 (22.2%)	193 (22.0%)	79 (21.4%)	1521 (24.3%)	23 (21.5%)	1577 (24.1%)	3 (42.9%)	1600 (24.1%)
70-79	1656 (33.9%)	262 (30.1%)	254 (29.0%)	109 (29.5%)	2063 (32.9%)	40 (37.4%)	2132 (32.6%)	2 (28.6%)	2172 (32.7%)
80-90	826 (16.9%)	138 (15.8%)	177 (20.2%)	47 (12.7%)	1094 (17.4%)	14 (13.1%)	1127 (17.3%)	0 (0.0%)	1141 (17.2%)
MPN subtype
PV	2213 (45.2%)	32 (3.7%)	80 (9.1%)	4 (1.1%)	2321 (37.0%)	1 (0.9%)	2324 (35.6%)	0 (0.0%)	2325 (35.0%)
ET	1823 (37.3%)	546 (62.7%)	502 (57.2%)	249 (67.3%)	2622 (41.8%)	71 (66.4%)	2800 (42.9%)	4 (57.1%)	2871 (43.2%)
PMF	440 (9.0%)	200 (23.0%)	170 (19.4%)	96 (25.9%)	714 (11.4%)	25 (23.4%)	785 (12.0%)	0 (0.0%)	810 (12.2%)
MPN-U	416 (8.5%)	93 (10.7%)	125 (14.3%)	21 (5.7%)	613 (9.8%)	10 (9.3%)	624 (9.6%)	3 (42.9%)	634 (9.5%)
Calendar period of diagnosis
2008-2014	2080 (42.5%)	145 (16.6%)	696 (79.4%)	16 (4.3%)	2905 (46.3%)	8 (7.5%)	2913 (44.6%)	0 (0.0%)	2921 (44.0%)
2015-2021	2812 (57.5%)	726 (83.4%)	181 (20.6%)	354 (95.7%)	3365 (53.7%)	99 (92.5%)	3620 (55.4%)	7 (100.0%)	3719 (56.0%)
Event of interest
AML/MDS	308 (6.3%)	50 (5.7%)	102 (11.6%)	7 (1.9%)	453 (7.2%)	5 (4.7%)	455 (7.0%)	1 (14.3%)	460 (6.9%)
AML	193 (3.9%)	34 (3.9%)	63 (7.2%)	5 (1.4%)	285 (4.5%)	2 (1.9%)	288 (4.4%)	1 (14.3%)	290 (4.4%)
MDS	137 (2.8%)	19 (2.2%)	44 (5.0%)	2 (0.5%)	198 (3.2%)	3 (2.8%)	197 (3.0%)	0 (0.0%)	200 (3.0%)

7 Statistical Software

The statistical software used for the analysis was R version 4.3.1.